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The maximum similarity partitioning problem and its application in the transcriptome reconstruction and quantification problem

机译:最大相似度划分问题及其在转录组重建和量化问题中的应用

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摘要

Reconstruct and quantify the RNA molecules in a cell at a given moment is an important problem in molecular biology that allows one to know which genes are being expressed and at which intensity level. Such problem is known as transcriptome reconstruction and quantification problem (TRQP). Although several approaches were already designed for the TRQP, none of them model it as a combinatorial optimisation problem over strings. In order to narrow this gap, we present here a new combinatorial optimisation problem called maximum similarity partitioning problem (MSPP) that models the TRQP. In addition, we prove that the MSPP is NP-complete in the strong sense and present a greedy heuristic for it and some experimental results.
机译:在给定的时刻重建和定量细胞中的RNA分子是分子生物学中的一个重要问题,它使人们可以知道正在表达的基因和强度。这种问题被称为转录组重建和量化问题(TRQP)。尽管已经为TRQP设计了几种方法,但是没有一种方法将其建模为字符串上的组合优化问题。为了缩小这一差距,我们在这里提出了一个新的组合优化问题,称为最大相似度划分问题(MSPP),该问题对TRQP进行了建模。此外,我们证明了MSPP在强意义上是NP完全的,并对其进行了贪婪的启发式实验和一些实验结果。

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